---
license: apache-2.0
base_model: facebook/convnextv2-base-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-base-1k-224-finetuned-cassava-leaf-disease
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8845794392523364
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# convnextv2-base-1k-224-finetuned-cassava-leaf-disease

This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3329
- Accuracy: 0.8846

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 240
- eval_batch_size: 240
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 960
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.7644        | 0.99  | 20   | 1.5288          | 0.6140   |
| 0.8358        | 1.98  | 40   | 0.6582          | 0.7584   |
| 0.5367        | 2.96  | 60   | 0.4823          | 0.8229   |
| 0.4645        | 4.0   | 81   | 0.4269          | 0.8556   |
| 0.4218        | 4.99  | 101  | 0.3912          | 0.8659   |
| 0.391         | 5.98  | 121  | 0.3637          | 0.8748   |
| 0.3789        | 6.96  | 141  | 0.3554          | 0.8748   |
| 0.3684        | 8.0   | 162  | 0.3489          | 0.8790   |
| 0.3671        | 8.99  | 182  | 0.3503          | 0.8813   |
| 0.3545        | 9.98  | 202  | 0.3442          | 0.8818   |
| 0.339         | 10.96 | 222  | 0.3369          | 0.8841   |
| 0.3225        | 12.0  | 243  | 0.3424          | 0.8808   |
| 0.3228        | 12.99 | 263  | 0.3386          | 0.8850   |
| 0.3141        | 13.98 | 283  | 0.3344          | 0.8846   |
| 0.3219        | 14.81 | 300  | 0.3329          | 0.8846   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1